Left Ventricular Mass is Independently Related to Coronary Artery Atherosclerotic Burden
Bibliographic record
Abstract
BACKGROUND: Left ventricular mass (LVM) is a predictor for adverse cardiovascular outcomes. Coronary atherosclerosis (coronary artery disease [CAD]) and concentric left ventricular (LV) remodeling are linked pathophysiologically by endothelial dysfunction. AIM: This study sought to determine the potential association between coronary atherosclerosis and LVM. METHODS: A total of 2384 consecutive patients, without structural heart disease or a medical history of CAD, undergoing prospective mid-diastolic electrocardiogram-gated computed tomography coronary angiography were enrolled in the study. LVM and LV mid-diastolic volume were measured using semiautomated software and indexed to body surface area. The average LV mid-diastolic wall thickness and concentricity index (LVM/LV mid-diastolic volume) were calculated. According to the Agatston Score, the patients were divided into 3 groups (Agatston=0, 0.1 to 399.9, ≥400). Similarly, patients were also divided into 4 groups on the basis of the Total Plaque Score (TPS) (0, 1 to 4, 5 to 8, and ≥9). In addition, patients were categorized according to CAD (normal coronaries, nonobstructive CAD, and obstructive stenosis [obstruction >50%]). The association between the different categories of CAD and LV measures was assessed. RESULTS: Both left ventricular mass index (LVMi) and the LV concentricity index increased with TPS categories from 55.3±12.1, 57.4±11.7, 60.9±13.6, and 63.7±15.3 g/m2 (P<0.05), and 0.935±0.424, 0.975±0.3273, 1.046±0.431, and 1.138±0.443 mL/g (P<0.01), respectively. A similar trend of increasing LVMi was observed with increasing Agatston Score (P<0.001) and CAD category (P<0.05). CONCLUSION: In patients without known structural heart disease, LVMi is independently associated with measures of CAD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".